As shown in Table REF , TVT+SAFF achieves the best performance, which proves the effectiveness of the proposed SAFF. DANN [1]} achieves the worst results since it uses a gradient reversal layer to learn invariant features between domains for adversarial adaptation, which may weaken the difference between categories, resulting in lower recognition ability. MCD [2]} and CDAN+E [3]} further exploit discriminative information conveyed in the classifier predictions to assist adversarial adaptation, improving classification accuracy by 25.3\(\%\)  and 28.7\(\%\)  respectively.
